2 PhD student positions for fetal brain MRI

Radiology Department of University of Lausanne
Location: 
Lausanne, Switzerland
Job Type: 
Full Time
Closing Date: 
Friday, January 11, 2019

We are looking for two motivated students for a PhD candidacy positions (4 years funding with annual renewal of contract) at the Medical Image Analysis Laboratory of the Radiology Department and Center for Biomedical Imaging, Lausanne University.

Description: We look for two PhD student candidates that will work jointly with a post-doctoral researcher expert in MR physics and under the direction of Dr. Meritxell Bach Cuadra. The two PhD thesis projects are:

  1. the development machine learning segmentation methods for the fetal brain analysis and their integration to a joint segmentation-super-resolution reconstruction of T2-weighted and T2 quantitative images of the fetal brain.
  2. The development of an image processing pipeline for the super-resolution reconstruction of diffusion fetal brain MRI, including the exploration of new acquisition schemes on phantom data.

Your profile:

  • You should have a master's (MSc) degree in physics, computer science, or electrical engineering, or similar degree with an equivalent academic level.
  • A genuine interest in signal and image processing and machine learning techniques is a must.
  • Strong mathematical background.
  • Good programing skills in C++, ITK and Python (knowledge of MevisLab is a plus).
  • Prior exposure to medical imaging and or neuroimaging is a plus.
  • Good skills in English (oral and written).
  • Rigorous work habits, a curious and critical mind, and a good sense of initiative.
  • A high-level perseverance and a strong personal commitment are expected.

We offer:

  • a multidisciplinary project between cutting-edge brain imaging and advanced image processing, MR physics, and clinical context.
  • an extremely stimulating field of research within a highly specialized and qualified scientific environment.
  • Access to state-of-the-art clinical MRI scanners.

Gross salary (pre-employer/employee tax): in compliance with Swiss National Science Foundation and UNIL.

Successful applications are subject to academic approval from the UNIL and Doctoral School; the selected candidate will be enrolled in Life Science Doctoral School at UNIL.